Azimuthal solar synchronization and aerodynamic neuro-optimization: an empirical study on slime-mold-inspired neural networks for solar UAV range optimization

This study introduces a novel methodology for enhancing the efficiency of solar-powered unmanned aerial vehicles (UAVs) through azimuthal solar synchronization and aerodynamic neurooptimization, leveraging the principles of slime mold neural networks. The objective is to broaden the operational capa...

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Main Authors: Graheeth, Hazare, Mohamed Thariq, Hameed Sultan, Dariusz, Mika, Farah Syazwani, Shahar, Grzegorz, Skorulski, Marek, Nowakowski, Andriy, Holovatyy, Ile, Mircheski, Wojciech, Giernacki
Format: Article
Language:English
Published: Multidisciplinary Digital Publishing Institute 2024
Online Access:http://psasir.upm.edu.my/id/eprint/114480/
http://psasir.upm.edu.my/id/eprint/114480/1/114480.pdf
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author Graheeth, Hazare
Mohamed Thariq, Hameed Sultan
Dariusz, Mika
Farah Syazwani, Shahar
Grzegorz, Skorulski
Marek, Nowakowski
Andriy, Holovatyy
Ile, Mircheski
Wojciech, Giernacki
author_facet Graheeth, Hazare
Mohamed Thariq, Hameed Sultan
Dariusz, Mika
Farah Syazwani, Shahar
Grzegorz, Skorulski
Marek, Nowakowski
Andriy, Holovatyy
Ile, Mircheski
Wojciech, Giernacki
author_sort Graheeth, Hazare
building UPM Institutional Repository
collection Online Access
description This study introduces a novel methodology for enhancing the efficiency of solar-powered unmanned aerial vehicles (UAVs) through azimuthal solar synchronization and aerodynamic neurooptimization, leveraging the principles of slime mold neural networks. The objective is to broaden the operational capabilities of solar UAVs, enabling them to perform over extended ranges and in varied weather conditions. Our approach integrates a computational model of slime mold networks with a simulation environment to optimize both the solar energy collection and the aerodynamic performance of UAVs. Specifically, we focus on improving the UAVs’ aerodynamic efficiency in flight, aligning it with energy optimization strategies to ensure sustained operation. The findings demonstrated significant improvements in the UAVs’ range and weather resilience, thereby enhancing their utility for a variety of missions, including environmental monitoring and search and rescue operations. These advancements underscore the potential of integrating biomimicry and neuralnetwork-based optimization in expanding the functional scope of solar UAVs.
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institution Universiti Putra Malaysia
institution_category Local University
language English
last_indexed 2025-11-15T14:21:41Z
publishDate 2024
publisher Multidisciplinary Digital Publishing Institute
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spelling upm-1144802025-01-22T02:17:44Z http://psasir.upm.edu.my/id/eprint/114480/ Azimuthal solar synchronization and aerodynamic neuro-optimization: an empirical study on slime-mold-inspired neural networks for solar UAV range optimization Graheeth, Hazare Mohamed Thariq, Hameed Sultan Dariusz, Mika Farah Syazwani, Shahar Grzegorz, Skorulski Marek, Nowakowski Andriy, Holovatyy Ile, Mircheski Wojciech, Giernacki This study introduces a novel methodology for enhancing the efficiency of solar-powered unmanned aerial vehicles (UAVs) through azimuthal solar synchronization and aerodynamic neurooptimization, leveraging the principles of slime mold neural networks. The objective is to broaden the operational capabilities of solar UAVs, enabling them to perform over extended ranges and in varied weather conditions. Our approach integrates a computational model of slime mold networks with a simulation environment to optimize both the solar energy collection and the aerodynamic performance of UAVs. Specifically, we focus on improving the UAVs’ aerodynamic efficiency in flight, aligning it with energy optimization strategies to ensure sustained operation. The findings demonstrated significant improvements in the UAVs’ range and weather resilience, thereby enhancing their utility for a variety of missions, including environmental monitoring and search and rescue operations. These advancements underscore the potential of integrating biomimicry and neuralnetwork-based optimization in expanding the functional scope of solar UAVs. Multidisciplinary Digital Publishing Institute 2024-09-13 Article PeerReviewed text en cc_by_4 http://psasir.upm.edu.my/id/eprint/114480/1/114480.pdf Graheeth, Hazare and Mohamed Thariq, Hameed Sultan and Dariusz, Mika and Farah Syazwani, Shahar and Grzegorz, Skorulski and Marek, Nowakowski and Andriy, Holovatyy and Ile, Mircheski and Wojciech, Giernacki (2024) Azimuthal solar synchronization and aerodynamic neuro-optimization: an empirical study on slime-mold-inspired neural networks for solar UAV range optimization. Applied Sciences, 14 (18). art. no. 8265. pp. 1-19. ISSN 2076-3417 https://www.mdpi.com/2076-3417/14/18/8265 10.3390/app14188265
spellingShingle Graheeth, Hazare
Mohamed Thariq, Hameed Sultan
Dariusz, Mika
Farah Syazwani, Shahar
Grzegorz, Skorulski
Marek, Nowakowski
Andriy, Holovatyy
Ile, Mircheski
Wojciech, Giernacki
Azimuthal solar synchronization and aerodynamic neuro-optimization: an empirical study on slime-mold-inspired neural networks for solar UAV range optimization
title Azimuthal solar synchronization and aerodynamic neuro-optimization: an empirical study on slime-mold-inspired neural networks for solar UAV range optimization
title_full Azimuthal solar synchronization and aerodynamic neuro-optimization: an empirical study on slime-mold-inspired neural networks for solar UAV range optimization
title_fullStr Azimuthal solar synchronization and aerodynamic neuro-optimization: an empirical study on slime-mold-inspired neural networks for solar UAV range optimization
title_full_unstemmed Azimuthal solar synchronization and aerodynamic neuro-optimization: an empirical study on slime-mold-inspired neural networks for solar UAV range optimization
title_short Azimuthal solar synchronization and aerodynamic neuro-optimization: an empirical study on slime-mold-inspired neural networks for solar UAV range optimization
title_sort azimuthal solar synchronization and aerodynamic neuro-optimization: an empirical study on slime-mold-inspired neural networks for solar uav range optimization
url http://psasir.upm.edu.my/id/eprint/114480/
http://psasir.upm.edu.my/id/eprint/114480/
http://psasir.upm.edu.my/id/eprint/114480/
http://psasir.upm.edu.my/id/eprint/114480/1/114480.pdf